The present invention relates to business to business market price control and management systems. More particularly, the present invention relates to systems and methods for generating pricing power and risk scores for business segments in order to facilitate the optimizing of prices in a business to business market setting wherein an optimal price change is determined according to business strategy and objectives.
There are major challenges in business to business (hereinafter “B2B”) markets which hinder the effectiveness of classical approaches to price optimization. These classical approaches to price optimization typically rely upon databases of extensive transaction data which may then be modeled for demand. The effectiveness of classical price optimization approaches depends upon a rich transaction history where prices have changed, and consumer reactions to these price changes are recorded. Thus, classical price optimization approaches work best where there is a wide customer base and many products, such as in Business to Consumer (B2C) settings.
Unlike B2C environments, in B2B markets a small number of customers represent the lion's share of the business. Managing the prices of these key customers is where most of the pricing opportunity lies. Also, B2B markets are renowned for being data-poor environments. Availability of large sets of accurate and complete historical sales data is scarce.
Furthermore, B2B markets are characterized by deal negotiations instead of non-negotiated sale prices (prevalent in business to consumer markets). There is no existing literature on optimization of negotiation terms and processes, neither at the product/segment level nor at the customer level.
Finally, B2B environments suffer from poor customer segmentation. Top-down price segmentation approaches are rarely the answer. Historical sales usually exhibit minor price changes for each customer. Furthermore, price bands within customer segments are often too large and customer behavior within each segment is non-homogeneous.
Product or segment price optimization relies heavily on the quality of the customer segmentation and the availability of accurate and complete sales data. In this context, price optimization makes sense only (i) when price behavior within each customer segment is homogeneous and (ii) in the presence of data-rich environments where companies sales data and their competitors' prices are readily available. These conditions are met almost exclusively in business to consumer (hereinafter “B2C”) markets such as retail, and are rarely encountered in B2B markets.
On the other hand, customer price optimization relies heavily on the abundance of data regarding customers' past behavior and experience, including win/loss data and customer price sensitivity. Financial institutions have successfully applied customer price optimization in attributing and setting interest rates for credit lines, mortgages and credit cards. Here again, the aforementioned condition is met almost exclusively in B2C markets.
There are three major types of price optimization solutions in the B2B marketplace: revenue/yield management, price testing and highly customized optimization solutions.
Revenue/yield management approaches were initially developed in the airline context, and were later expanded to other applications such as hotel revenue management, car rentals, cruises and some telecom applications (e.g. bandwidth pricing). These approaches are exclusively concerned with perishable products (e.g. airline seats) and are not pricing optimization approaches per se.
Price testing approaches attempt to learn and model customer behavior dynamically by measuring customer reaction to price changes. While this approach has been applied rather successfully in B2C markets, where the benefits of price optimization outweigh the loss of a few customers, its application to B2B markets is questionable. No meaningful customer behavior can be modeled without sizable changes in customer prices (both price increases and decreases). In B2B markets, where a small fraction of customers represent a substantial fraction of the overall business, these sizable price-changing tests can have adverse impact on business. High prices can drive large customers away with potentially a significant loss of volume. Low prices on the other hand, even for short periods of time, can dramatically impact customer behavior, increase customers' price sensitivities and trigger a more strategic approach to purchasing from the customers' side.
Finally, in B2B markets, highly customized price optimization solutions have been proposed. These solutions have had mixed results. These highly customized price optimization solutions require significant consulting effort in order to address companies' unique situations including cost structure, customer and competitor behavior, and to develop optimization methods that are tailored to the type of pricing data that is available. Most of the suggested price changes from these solutions are not implemented. Even when they are implemented, these price changes tend not to stick. Furthermore, the maintenance of such pricing solutions usually requires a lot of effort. This effort includes substantial and expensive on-going consulting engagements with the pricing companies.
Due to the difficulties inherent in a B2B environment, there is a strong need for a system able to provide guidance for price changes which reduces the need for ongoing consultation and is more readily implemented.
Furthermore, instead of developing highly customized company-specific price optimization solutions, there remains a need for scalable and customizable price optimization solutions that vary by industry vertical.
In view of the foregoing, System and Methods for Calibrating Pricing Power and Risk Scores are disclosed. The present invention provides a novel system for price guidance is put forward which leverages multiple predictive factors to calibrate two values known as business segment “Pricing Risk” and “Pricing Power”. Calibrated Pricing Risk and Pricing Power may be used by a price management system to provide negotiation guidance, price allocation data and business decision guidance.
Utilizing Pricing Power and Pricing Risk enables clients in a B2B environment to generate efficient pricing guidance without the need for a particularly rich transaction database. Additionally, Pricing Power and Pricing Risk may be leveraged to provide guidance to clients with a great reduction in the invasive, expensive and time consuming consultation typically required when generating highly customized price optimization solutions.